Psychiatric symptoms are the strongest predictors of quality of life in patients with drug-resistant epilepsy or psychogenic nonepileptic seizures

The Most Frequent Psychiatric Comorbidities in Bulgarian Patients With Epilepsy: Their Connection With the Main Clinical Characteristics and Quality of Life

AIM

 The objective of this study is to determine and compare the relationship of the most common psychiatric comorbidities in Bulgarian patients with epilepsy with the main clinical characteristics, as well as to evaluate their impact on certain aspects of the quality of life.

CLINICAL RATIONALE

 Psychiatric comorbidities occur in about one-third of people with epilepsy throughout their lifetime, and their incidence is much greater in high-risk groups such as patients with treatment-resistant epilepsy.

MATERIAL AND METHODS

 The study group consisted of 129 participants, of whom 104 were divided into four groups according to the presence of one of the most frequently diagnosed psychiatric comorbidities in our patients with epilepsy: personality and behavioral disorder (PBD) (n=25), mild to moderate depressive disorder (n=26), anxiety disorder (n=32), and dissociative and conversion disorders (n=21). A control group was also formed with a similar number of participants with epilepsy (n=25) without psychiatric comorbidity. Some sociodemographic and clinical characteristics of epilepsy were analyzed in all patients. All patients filled out two questionnaires: the Bulgarian version of quality of life in epilepsy - 89 (QOLIE-89) and the Bulgarian version of SIDAED (assessing SIDe effects in antiepileptic drugs (AED) treatment).

RESULTS

 The analysis revealed a negative influence of psychiatric comorbidity on the presence of epileptic seizures, unwanted drug effects, and lower scores for all aspects of the quality of life of patients with epilepsy.

CONCLUSION AND CLINICAL IMPLICATIONS

 The main conclusion of our study is the presence of an interaction between psychiatric comorbidity, the clinical course of the disease, and the deteriorated quality of life (QOL) in patients with epilepsy. Further attention, comprehensive care, and targeted research are needed to analyze individual psychiatric comorbidities in patients with epilepsy for early detection and treatment.

Evaluation of quality of life's prognostic factors in people with functional seizures

AIMS

Functional non-epileptic seizures significantly impact the quality of life of patients. We aimed to identify prognostic factors associated with the quality of life in individuals with functional non-epileptic seizures.

SUBJECTS AND METHODS

Adult patients diagnosed with definite or documented functional seizures based on LaFrance's criteria (n=72) were enrolled at the time of diagnosis. Quality of life was assessed using the Quality of Life in Epilepsy Inventory-31 (QOLIE-31) at diagnosis and at a six-month follow-up. Demographic and medical information was collected, and psychiatric comorbidities were evaluated using validated scales.

RESULTS

Comparisons between diagnosis and follow-up did not reveal any factors associated with improvement in quality of life at six months after diagnosis. However, multivariable analysis, adjusted for age, sex, diagnosis delay, and frequency of functional seizures showed a significant cross-sectional relationship with a QOLIE-31 score decrease of 0.66 [95% CI -0.93;-0.39], -0.32 [-0.61; -0.03], and -0.22 [-0.42; -0.02] for an increase of 1 point of BDI-2 score, BAI score, and CTQ score respectively.

CONCLUSION

Psychiatric comorbidities, particularly depression and anxiety, are associated with worse quality of life in patients with functional seizures. This underscores the crucial importance of multidisciplinary care involving both neurological and psychiatric expertise when managing individuals with functional seizures.

The impact of the comorbid seizure/epilepsy on the health related quality of life in people with multiple sclerosis: an international multicentric study

Introduction

The health-related quality of life (HRQoL) of people with (Pw) multiple sclerosis (MS) is usually deteriorated. It has been recently suggested that comorbidities may have the negative influence on the quality of life of the PwMS, but according to the best of our knowledge, only one study investigated, although in a very small cohort, the impact of individual comorbidity on the quality of life of PwMS. The aim of our investigation was to assess, in an international, multicentric study, the impact of comorbid seizure/epilepsy on the HRQoL in PwMS.

Methods

We conducted cross-sectional study at numerous neurological centers in Serbia, Croatia, Bulgaria, Montenegro, Northern Macedonia, and Bosnia and Herzegovina (Federation of Bosnia and Herzegovina and Republic of Srpska). For each patient, demographic and clinical data were collected, including Expanded disability status scale (EDSS) score. Beck Depression Inventory (BDI) and the 36-Item Short Form Health Survey (SF-36) questionnaires were administered to all patients.

Results

The study comprised 326 PwMS in total, 127 PwMS with seizure/epilepsy and 209 PwMS without. Both mean Physical health composite (PHC) and mental health composite (MHC) scores, were statistically significantly higher in PwMS without seizure/epilepsy, implicating worse quality of life in PwMS with comorbid seizure/epilepsy. Presence of seizure/epilepsy in pwMS was statistically significant independent predictor of both PHC and MHC, in multivariate linear regression model after adjustment for potential confounding variables. The hierarchical multivariate regression analysis was performed in order to establish the most important predictors of the PHC and MHC of the SF-36, in PwMS with seizure/epilepsy; older age, higher level of disability, as measured by EDSS, higher depression score, drug-resistant epilepsy and shorter time since last seizure were found to significantly predict worse MHC score in PwMS with seizure/epilepsy.

Discussion

Our results point to the possible role of theinterventions related to the adequate control of epilepsy along with improvement of the mental health status to be important in order to reduce MS burden in the PwMS with comorbid seizure/epilepsy.

Machine learning using multimodal clinical, electroencephalographic, and magnetic resonance imaging data can predict incident depression in adults with epilepsy: A pilot study

OBJECTIVE

This study was undertaken to develop a multimodal machine learning (ML) approach for predicting incident depression in adults with epilepsy.

METHODS

We randomly selected 200 patients from the Calgary Comprehensive Epilepsy Program registry and linked their registry-based clinical data to their first-available clinical electroencephalogram (EEG) and magnetic resonance imaging (MRI) study. We excluded patients with a clinical or Neurological Disorders Depression Inventory for Epilepsy (NDDI-E)-based diagnosis of major depression at baseline. The NDDI-E was used to detect incident depression over a median of 2.4 years of follow-up (interquartile range [IQR] = 1.5-3.3 years). A ReliefF algorithm was applied to clinical as well as quantitative EEG and MRI parameters for feature selection. Six ML algorithms were trained and tested using stratified threefold cross-validation. Multiple metrics were used to assess model performances.

RESULTS

Of 200 patients, 150 had EEG and MRI data of sufficient quality for ML, of whom 59 were excluded due to prevalent depression. Therefore, 91 patients (41 women) were included, with a median age of 29 (IQR = 22-44) years. A total of 42 features were selected by ReliefF, none of which was a quantitative MRI or EEG variable. All models had a sensitivity > 80%, and five of six had an F1 score ≥ .72. A multilayer perceptron model had the highest F1 score (median = .74, IQR = .71-.78) and sensitivity (84.3%). Median area under the receiver operating characteristic curve and normalized Matthews correlation coefficient were .70 (IQR = .64-.78) and .57 (IQR = .50-.65), respectively.

SIGNIFICANCE

Multimodal ML using baseline features can predict incident depression in this population. Our pilot models demonstrated high accuracy for depression prediction. However, overall performance and calibration can be improved. This model has promise for identifying those at risk for incident depression during follow-up, although efforts to refine it in larger populations along with external validation are required.

Association between depressive and anxious symptoms with cognitive function and quality of life in drug-resistant epilepsy

•Depressive/anxious disorders and cognitive impairment are frequent comorbidities in epilepsy and have a more deleterious effect in DRE.•Studies concerning the relationship between anxiety and depression and cognitive performance in DRE are scarce.•Higher scores in HADS are associated with lower QOLIE-31 scores and might be considered as predictors of QOL in DRE.•A relationship between anxious and depressive symptoms -measured with HADS and SCL-90R- and cognition might not exist.•There remains an unexplored study area regarding this relationship which requires more attention to improve the assessment of DRE.

Nose-to-brain delivery of perampanel formulated in a self-microemulsifying drug delivery system improves anticonvulsant and anxiolytic activity in mice

Perampanel (PER) is a potent third-generation antiepileptic drug only available for oral administration. Additionally, PER has shown potential in managing epilepsy comorbidities such as anxiety. Previously, we demonstrated that the intranasal (IN) administration of PER, loaded in a self-microemulsifying drug delivery system (SMEDDS), improved brain-targeting and exposure in mice. Herein, we investigated PER brain biodistribution, its anticonvulsant and anxiolytic effects, and its potential olfactory and neuromotor toxicity after IN administration to mice (1 mg/kg). PER showed a rostral-caudal brain biodistribution pattern when administered intranasally. At short times post-nasal dosing, high PER concentrations were found in olfactory bulbs (olfactory bulbs/plasma ratios of 1.266 ± 0.183 and 0.181 ± 0.027 after IN and intravenous administrations, respectively), suggesting that a fraction of the drug directly reaches brain through the olfactory pathway. In maximal electroshock seizure test, IN PER protected 60% of mice against seizure development, a substantially higher value than the 20% protected after receiving oral PER. . PER also demonstrated anxiolytic effects in open field and elevated plus maze tests. Buried food-seeking test showed no signs of olfactory toxicity. Neuromotor impairment was found in rotarod and open field tests at the times of PER maximum concentrations after IN and oral administrations. Nevertheless, neuromotor performance was improved after repeated administrations. Compared with IN vehicle, PER IN administration decreased brain levels of L-glutamate (0.91 ± 0.13 mg/mL vs 0.64 ± 0.12 mg/mL) and nitric oxide (100 ± 15.62% vs 56.62 ± 4.95%), without interfering in GABA levels. Altogether, these results suggest that the IN PER delivery through the developed SMEDDS can be a safe and promising alternative to oral treatment, which support the design of clinical studies to evaluate the IN PER delivery to treat epilepsy and neurological-related conditions as anxiety.

Clinical relevance of interictal dysphoric disorder and its impact on quality of life in drug-resistant epilepsy

OBJECTIVE

This study aims to assess the prevalence of Interictal Dysphoric Disorder (IDD) in drug-resistant epilepsy (DRE) and to describe its clinical and psychopathological profile, including personality, as well as its impact on quality of life (QOL).

METHOD

A retrospective cross-sectional study from an Epilepsy Unit from January 2007 to December 2017. All patients were diagnosed with DRE. Patients underwent a battery of tests (HADS, SCL-90R, PDQ-4+, QOLIE-31) and a psychiatrist assessed the presence of Axis-I disorders and IDD. Statistical procedures were carried out using R-4.0.1 software.

RESULTS

A total of 282 patients were included. A statistically significant association was found between IDD and mood and anxiety disorders (p < 0.001 and p < 0.05 respectively), and between IDD and higher scores in all HADS and SCL-90-R items compared to subjects without IDD (p < 0.001). A statistically significant association was also found between IDD and obsessive-compulsive, borderline and depressive personality disorder (p < 0.05). Scores in all QOLIE-31 items except for 'medication effects' were significantly lower in subjects with IDD compared with subjects without IDD (p < 0.001).

CONCLUSIONS

In DRE, IDD subjects show differences in the psychopathological profile and QOL scores compared to subjects without a diagnosis of IDD. An early diagnosis of IDD could facilitate prompt interventions which might positively impact QOL.

Closed-Loop Neuromodulation and Self-Perception in Clinical Treatment of Refractory Epilepsy

Background: Newer "closed-loop" neurostimulation devices in development could, in theory, induce changes to patients' personalities and self-perceptions. Empirically, however, only limited data of patient and family experiences exist. Responsive neurostimulation (RNS) as a treatment for refractory epilepsy is the first approved and commercially available closed-loop brain stimulation system in clinical practice, presenting an opportunity to observe how conceptual neuroethical concerns manifest in clinical treatment.Methods: We conducted ethnographic research at a single academic medical center with an active RNS treatment program and collected data via direct observation of clinic visits and in-depth interviews with 12 patients and their caregivers. We used deductive and inductive analyses to identify the relationship between these devices and patient changes in personality and self-perception.Results: Participants generally did not attribute changes in patients' personalities or self-perception to implantation of or stimulation using RNS. They did report that RNS affected patients' experiences and conceptions of illness. In particular, the capacity to store and display electrophysiological data produced a common frame of reference and a shared vocabulary among patients and clinicians.Discussion: Empirical experiences of a clinical population being treated with closed-loop neuromodulation do not corroborate theoretical concerns about RNS devices described by neuroethicists and technology developers. However, closed-loop devices demonstrated an ability to change illness experiences. Even without altering identify and self-perception, they provided new cultural tools and metaphors for conceiving of epilepsy as an illness and of the process of diagnosis and treatment. These findings call attention to the need to situate neuroethical concerns in the broader contexts of patients' illness experiences and social circumstances.

Upper cerebellar glucose hypermetabolism in patients with temporal lobe epilepsy and interictal psychosis

OBJECTIVE

Psychosis is an important comorbidity in epilepsy, but its pathophysiology is still unknown. The imaging modality ¹⁸ F-fluorodeoxyglucose-positron emission tomography (¹⁸ F-FDG PET) is widely used to measure brain glucose metabolism, and we speculated that ¹⁸ F-FDG PET may detect characteristic alteration patterns in individuals with temporal lobe epilepsy (TLE) and psychosis.

METHODS

We enrolled 13 patients with TLE and interictal psychosis (TLE-P) and 21 patients with TLE without psychosis (TLE-N). All underwent interictal ¹⁸ F-FDG-PET scanning. Statistical Parametric Mapping (SPM)12 software was used for the normalization process, and we performed a voxel-wise comparison of the TLE-P and TLE-N groups.

RESULTS

Cerebral hypometabolic areas were observed in the ipsilateral temporal pole to hippocampus in both patient groups. In the TLE-P group, the voxel-wise comparison revealed significantly increased ¹⁸ F-FDG signals in the upper cerebellum, superior cerebellar peduncle, and midbrain. There were no significant between-group metabolic differences around the focus or other cerebral areas.

SIGNIFICANCE

Our results demonstrated significant hypermetabolism around the upper cerebellum in patients with TLE and interictal psychosis compared to patients with TLE without psychosis. These findings may reflect the involvement of the cerebellum in the underlying neurobiology of interictal psychosis and could contribute to a better understanding of this disorder.

Multimodal Quality of Life Assessment in Post-9/11 Veterans With Epilepsy: Impact of Drug Resistance, Traumatic Brain Injury, and Comorbidity

BACKGROUND AND OBJECTIVES

Epilepsy is defined by the occurrence of multiple unprovoked seizures, but quality of life (QOL) in people with epilepsy is determined by multiple factors, in which psychiatric comorbidities play a pivotal role. Therefore, understanding the interplay between comorbidities and QOL across epilepsy phenotypes is an important step towards improved outcomes. Here, we report the impact of QOL across distinct epilepsy phenotypes in a cohort of post-9/11 veterans with high rates of traumatic brain injury (TBI).

METHODS

This observational cohort study from the Veterans Health Administration included post-9/11 Veterans with epilepsy. A process integrating an epilepsy identification algorithm, chart abstraction, and self-reported measures was used to classify patients into one of four groups: 1. Epilepsy controlled with medications, 2. Drug resistant epilepsy (DRE), 3. Post-traumatic epilepsy (PTE), or 4. Drug resistant post-traumatic epilepsy (PT-DRE). Summary scores for six QOL measures were compared across the groups, adjusting for age, sex, and number of comorbidities.

RESULTS

A total of 529 survey respondents with epilepsy were included in the analysis: 249 controls (i.e., epilepsy without DRE or PTE), 124 with DRE, 86 with PTE, and 70 with PT-DRE. Drug resistant epilepsy was more common in those with PTE compared with non-traumatic epilepsy (45% vs. 33%, odds ratio 1.6 (95% CI: [1.1-2.4], p=0.01)). Patients with PTE and PT-DRE had significantly more comorbid conditions in health records than those with nontraumatic epilepsy. Those with both PTE and DRE reported the lowest QOL across all six measures, and this persisted after adjustment for comorbidities, and in further linear analyses.

DISCUSSION

Among those with PTE, DRE prevalence was significantly higher than for non-traumatic epilepsies. PTE was also associated with higher burden of comorbidity, and worse overall QOL compared to those with non-traumatic epilepsies. People with PTE are distinctly vulnerable to the comorbidities associated with TBI and epilepsy. This at-risk group should be the focus of future studies aimed at elucidating the factors associated with adverse health outcomes and developing anti-epileptogenic therapies.

Quality of life for patients with psychogenic nonepilepsy seizures in comparison with age- and gender-matched patients with epilepsy - Cross-sectional study

AIMS

Patients with psychogenic nonepileptic seizures (PNES), and age- and gender-matched patients with epilepsy (PWE) who utilized an out-patient service were compared regarding quality of life (QoL) and self-reported symptoms of depression. Additionally, the impact of miscellaneous clinical variables including symptoms of depression on QoL in patients with PNES and PWE in real-world settings was assessed.

SUBJECTS AND METHODS

Adult patients who had a diagnosis of definite or documented PNES based on LaFrance's criteria (PNES group, n = 62), or of epilepsy based on results of clinical and EEG procedures (Epilepsy group, n = 61) were enrolled. To assess QoL and evaluate depression, the Quality of Life in Epilepsy Inventory-10 (QOLIE-10) and Neurological Disorders Depression Inventory for Epilepsy (NDDI-E), respectively, were administered.

RESULTS

Comparisons between the groups revealed a shorter duration of illness and fewer number of attacks in patients with PNES as compared to the Epilepsy group (p < 0.0001; p = 0.0003, respectively). There was no significant difference between the groups revealed by the QOLIE-10 (p = 0.141), while the patients with PNES tended to have higher NDDI-E scores (p = 0.068). Multiple regression analysis of QOLIE-10 results in the PNES group revealed that NDDI-E score was the sole significant contributor (β = -0.425 p = 0.001). In contrast, NDDI-E score as well as attack frequency had a significant impact on QOLIE-10 results in the Epilepsy group (β = -0.283 p = 0.026; β = -0.272 p = 0.031, respectively).

CONCLUSION

In PWE and patients with PNES who utilized an out-patient service, QoL did not differ significantly between those groups. For treating PNES, psychosocial factors may be a more appropriate indicator of therapeutic goal than attack frequency.

Functional seizures are not less important than epilepsy

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People with functional seizures often suffer from psychiatric comorbidities.

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People with FS report detrimental effects on social aspects of their lives.

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FS are associated with a considerable direct and indirect economic burden.

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FS have increased rates of mortality compared to healthy controls.

Functional seizures (FS) are frequently encountered in neurology clinics, often affect young adults, and have significant negative impacts on many aspects of a person’s life. In the current narrative review, we searched the literature regarding some of the consequences of FS (i.e., psychiatric comorbidities, social consequences, costs that are associated with the condition, cognitive impairment in patients with FS, the quality of life of the people with FS, and the increased risk of mortality that is associated with FS). Evidence shows that FS have significant negative consequences, comparable in their magnitude to those affecting patients with epilepsy. The clinical and scientific communities should take steps to address these consequences through clinical care and research that prioritizes, facilitates, and expedites evidence-based diagnosis and treatment for FS.

Utility of mental health and sleep screening questionnaires for patients admitted to a seizure monitoring unit

RATIONALE

Patients with seizure disorders have relatively high rates of comorbid psychological and sleep disorders. Because these can profoundly affect quality of life, early recognition and treatment are of potential benefit. As a quality improvement project, we evaluated the performance and utility of a set of mental health and sleep quality screening questionnaires in patients admitted to a VA seizure monitoring unit (SMU).

METHODS

Questionnaires, including the Beck Depression Inventory-II (BDI-II), the post-traumatic stress disorder (PTSD) checklist (PCL), the Quality of Life in Epilepsy Inventory-31 (QOLIE-31), and the Pittsburgh Sleep Quality Index (PSQI), were administered to 100 patients admitted to the Portland VAMC SMU. Scored results were entered into the electronic medical record (EMR) within 72 h of hospital admission. We assessed how many patients exceeded questionnaire cutoff scores, and whether these patients had prior mental health or sleep diagnoses or evaluations within the six months preceding admission. Following hospital discharge, providers completed a survey regarding the utility of the questionnaire results. We also reviewed EMR documented mental health and sleep visits during the six months following the SMU admission.

RESULTS

Forty-seven patients (47.5%) exceeded the cutoff score for the BDI-II, including 15 without an admission diagnosis of depression, and 14 who had not seen a mental health provider in the previous six months. Similarly, 33 patients (33.3%) exceeded the cutoff score for the PCL, including nine without a diagnosis of PTSD. Scores on the BDI-II and PCL were highly correlated with the QOLIE-31 total score (r = 0.7). Seventy patients (70.7%) exceeded the cutoff score for poor sleep quality, and 37 did not have a sleep disorder diagnosis. Providers indicated that the questionnaire results were moderately or very helpful in most cases and influenced discharge recommendations to patients and referring providers in more than 50% of cases. Discharge recommendations for mental health or sleep follow-up were associated with EMR documented consultations within the six months following SMU admission.

CONCLUSIONS

The results suggest that a standard set of screening questionnaires can identify SMU patients at risk for mental health and sleep disorders, including patients not currently diagnosed or recently evaluated. Questionnaire results were perceived as helpful by providers and influenced discharge recommendations. Given that these disorders are treatable and have a major influence on health-related quality of life, the effort to collect and document this information is well justified.

Behavioral phenotypes of temporal lobe epilepsy

Objective

To identity phenotypes of self‐reported symptoms of psychopathology and their correlates in patients with temporal lobe epilepsy (TLE).

Method

96 patients with TLE and 82 controls were administered the Symptom Checklist 90‐Revised (SCL‐90‐R) to characterize emotional‐behavioral status. The nine symptom scales of the SCL‐90‐R were analyzed by unsupervised machine learning techniques to identify latent TLE groups. Identified clusters were contrasted to controls to characterize their association with sociodemographic, clinical epilepsy, neuropsychological, psychiatric, and neuroimaging factors.

Results

TLE patients as a group exhibited significantly higher (abnormal) scores across all SCL‐90‐R scales compared to controls. However, cluster analysis identified three latent groups: (1) unimpaired with no scale elevations compared to controls (Cluster 1, 42% of TLE patients), (2) mild‐to‐moderate symptomatology characterized by significant elevations across several SCL‐90‐R scales compared to controls (Cluster 2, 35% of TLE patients), and (3) marked symptomatology with significant elevations across all scales compared to controls and the other TLE phenotype groups (Cluster 3, 23% of TLE patients). There were significant associations between cluster membership and demographic (education), clinical epilepsy (perceived seizure severity, bitemporal lobe seizure onset), and neuropsychological status (intelligence, memory, executive function), but with minimal structural neuroimaging correlates. Concurrent validity of the behavioral phenotype grouping was demonstrated through association with psychiatric (current and lifetime‐to‐date DSM IV Axis 1 disorders and current treatment) and quality‐of‐life variables.

Significance

Symptoms of psychopathology in patients with TLE are characterized by a series of discrete phenotypes with accompanying sociodemographic, cognitive, and clinical correlates. Similar to cognition in TLE, machine learning approaches suggest a developing taxonomy of the comorbidities of epilepsy.